Generalized Model Predictive Torque Control of Synchronous Machines

Abstract

This study presents a generalized model predictive torque control (GMPTC) method that applies to all types of synchronous machines (SMs). The GMPTC method aims to minimize both torque error and performance index (PI) while adhering to voltage and current constraints. The PI can be defined by any function to be minimized to enhance the SM drive's performance, such as copper loss and inverter loss. The GMPTC problem, a nonlinear optimization problem, is solved based on either a continuous control set or a finite control set using the augmented Lagrangian method. The GMPTC method guarantees optimal operation across all regions, including maximum torque per ampere, flux weakening, maximum current, and maximum torque per voltage, without needing additional controllers. The GMPTC method is practical, requiring only a few tuning parameters (four to five), making it easy to implement. The method's effectiveness is demonstrated by numerical control of a 385-W synchronous reluctance machine and experimental control of a 1-kW interior permanent magnet SM.